ArticleUser modeling and user-adapted interaction2023
A dichotomic approach to adaptive interaction for socially assistive robots.
Article in User modeling and user-adapted interaction, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 21 citations in OpenAlex.
- Automated planning and scheduling in robot-aided rehabilitation: a review.Journal of neuroengineering and rehabilitation · 2025Review
- Longitudinal changes following the introduction of socially assistive robots in nursing homes: a qualitative study with ICF framework and causal loop diagramming.BMC geriatrics · 2024Article
- Application of Social Robots in Healthcare: Review on Characteristics, Requirements, Technical Solutions.Sensors (Basel, Switzerland) · 2023Review
- Classifying human emotions in HRI: applying global optimization model to EEG brain signals.Frontiers in neurorobotics · 2023Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Socially assistive robotics (SAR) aims at designing robots capable of guaranteeing social interaction to human users in a variety of assistance scenarios that range, e.g., from giving reminders for medications to monitoring of Activity of Daily Living, from giving advices to promote an healthy lifestyle to psychological monitoring. Among possible users, frail older adults deserve a special focus as they present a rich variability in terms of both alternative possible assistive scenarios (e.g., hospital or domestic environments) and caring needs that could change over time according to their health conditions. In this perspective, robot behaviors should be customized according to properly designed
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.